v0.2.3 (#5)

fcapsy_experiments/__init__.py

@@ -1,7 +1,7 @@
 from .correlation_table import CorrelationTable
 from .correlations_box_plot import correlations_boxplots
 
-__version__ = "0.2.2"
+__version__ = "0.2.3"
 __author__ = "Tomáš Mikula"
 __email__ = "[email protected]"
 __license__ = "MIT license"

fcapsy_experiments/mca/__init__.py

@@ -0,0 +1 @@
+from .mca_concept import MCAConcept

fcapsy_experiments/mca/mca_concept.py

@@ -0,0 +1,109 @@
+import prince
+import pandas as pd
+import plotly.graph_objects as go
+import plotly.express as px
+import textwrap
+
+
+class MCAConcept:
+    def __init__(
+        self,
+        concept: "concepts.lattices.Concept",
+        n_components=2,
+        random_state=42,
+        n_iter=100,
+        color_by=None,
+    ) -> None:
+        self._concept = concept
+        self.concept_df = self._concept_df()
+        self.n_components = n_components
+        self._color_by = color_by
+
+        self.mca = prince.MCA(
+            n_components=n_components, random_state=random_state, n_iter=n_iter
+        )
+        self.mca.fit(self.concept_df)
+
+        self.concept_df_transformed = pd.DataFrame(
+            self.mca.transform(self.concept_df), index=self._concept.extent
+        )
+
+    def _concept_df(self):
+        label_domain = self._concept.lattice._context._intents
+        vectors = list(
+            map(
+                lambda x: label_domain.__getitem__(x).bools(),
+                self._concept._extent.iter_set(),
+            )
+        )
+
+        df = pd.DataFrame(
+            vectors,
+            dtype=int,
+            index=self._concept.extent,
+            columns=self._concept.lattice._context.properties,
+        )
+
+        return df.loc[:, (df != 0).any(axis=0)]
+
+    def to_plotly(self) -> "go.Figure":
+        """Generates plotly figure.
+
+        Returns:
+            go.Figure: figure
+        """
+
+        # need some love
+        data = self.concept_df_transformed.copy()
+
+        hover_data = {
+                "x": False,
+                "y": False,
+            }
+
+        if self._color_by is not None:
+            color_name = self._color_by[0]
+            data[color_name] = self._color_by[1]
+            hover_data[color_name] = ":.2f"
+        else:
+            color_name = None
+
+        if self.n_components == 3:
+            data = data.rename(columns={0: "x", 1: "y", 2: "z"})
+
+            hover_data["z"] = False
+
+            fig = px.scatter_3d(
+                data,
+                x="x",
+                y="y",
+                z="z",
+                hover_name=list(
+                    map(
+                        lambda txt: "<br>".join(textwrap.wrap(txt, width=50)),
+                        self.concept_df_transformed.index,
+                    )
+                ),
+                hover_data=hover_data,
+                color=color_name,
+                color_continuous_scale="Bluered",
+            )
+        else:
+            data = data.rename(columns={0: "x", 1: "y"})
+
+            fig = px.scatter(
+                data,
+                x=0,
+                y=1,
+                hover_name=list(
+                    map(
+                        lambda txt: "<br>".join(textwrap.wrap(txt, width=50)),
+                        self.concept_df_transformed.index,
+                    )
+                ),
+                hover_data=hover_data,
+                color=color_name,
+                color_continuous_scale="Bluered",
+            )
+
+        return fig

setup.py

@@ -3,7 +3,7 @@
 
 setup(
     name="fcapsy-experiments",
-    version="0.2.2",
+    version="0.2.3",
     author="Tomáš Mikula",
     author_email="[email protected]",
     description="Package of experiments for fcapsy library.",